Various techniques for recognizing a crowd in an image have been proposed. For example, PTL 1 describes a number-of-persons measurement device that measures the number of persons from a shot video of a crowd. The number-of-persons measurement device described in PTL 1 extracts a head of a person included in the image, based on a head model, connects head positions determined as the same person between frames by using a feature quantity such as position information and color distribution, and measures the number of persons from the connection result.
NPL 1 describes a method for estimating the number of persons in a crowd. The method described in NPL 1 seizes a crowd state including overlap of persons, by a crowd-patch that represents the crowd state by a local image, and performs recursive learning of the number of persons in the patch to thereby estimate the number of persons from a static image.
PTL 2 describes a traffic quantity measurement system capable of acquiring traffic quantity data at an examination target spot. The system described in PTL 2 identifies, from a captured image of a predetermined examination target region, a passerby in the examination target region, and determines the number of the passersby.